基于高斯模型的电网业务数据分布式存储方法研究  

On Distributed Storage Method of Power Grid Business Data Based on Gaussian Model

作　　者：高慧芳 GAO Huifang(Shuozhou Advanced Normal College,Shuozhou Shanxi 036002,China)

机构地区：[1]朔州师范高等专科学校,山西朔州036002

出　　处：《北京工业职业技术学院学报》2025年第1期18-21,共4页Journal of Beijing Polytechnic College

基　　金：山西省基础研究计划(自由探索类)青年项目(202203021222329)。

摘　　要：常规的集中式数据存储方法在面对大规模、高频率的数据存储需求时,存储的效率相对较低,为此提出了基于高斯模型的电网业务数据分布式存储方法。通过分析电网业务数据特征,强化存储效率,实现对数据信息多层级增删处理;采用分层扩展存储及存储复验的方式,建立高斯电网业务数据分布式存储模型,完成数据存储。测试结果表明:设计方法的实际存储功率相对较高,内存占用率和CPU占用率明显更低,具有较好的存储性能。The conventional centralized data storage methods have relatively low storage efficiency when facing large-scale and high-frequency data storage requirements.Therefore,a distributed storage method for power grid business data based on Gaussian Model is proposed.By analyzing the characteristics of power grid business data,the efficiency of storage is strengthened,and the multi-level addition and deletion of data information is realized.Establish a distributed storage model for Gaussian power grid business data using a hierarchical expansion storage and storage verification approach to complete data storage.The test results show that the designed method has relatively high actual storage power,significantly lower memory and CPU usage,and good storage performance.

关 键 词：高斯模型 电网业务 业务数据 分布式存储 存储方法 数据整合 

分 类 号：TM744[电气工程—电力系统及自动化]